Abstract
There is a need to validate existing global cropland maps since they are used for different purposes including agricultural monitoring and assessment. In this paper we validate three recent global products (ESA-CCI, GlobeLand30, FROM-GC) and one regional product (Tanzania Land Cover 2010 Scheme II) using a validation data set that was collected by students through the Geo-Wiki tool. The ultimate aim was to understand the usefulness of these products for agricultural monitoring. Data were collected wall-to-wall for Kilosa district and for a sample across Tanzania. The results show that the amount of and spatial extent of cropland in the different products differs considerably from 8% to 42% for Tanzania, with similar values for Kilosa district. The agreement of the validation data with the four different products varied between 36% and 54% and highlighted that cropland is overestimated by the ESA-CCI and underestimated by FROM-GC. The validation data were also analyzed for consistency between the student interpreters and also compared with a sample interpreted by five experts for quality assurance. Regarding consistency between the students, there was more than 80% agreement if one difference in cropland category was considered (e.g., between low and medium cropland) while most of the confusion with the experts was also within one category difference. In addition to the validation of current cropland products, the data set collected by the students also has potential value as a training set for improving future cropland products.
Highlights
To ensure global food security, cropland is regularly monitored by initiatives such as GEOGLAM (Group on Earth Observation’s Global Agricultural Monitoring) [1], CropWatch [2], and the MARS (Monitoring Agricultural Resources) unit of the Joint Research Centre of the European Commission, among others [3]
The validation data set collected by the students is presented in the results as the average cropland values from different in Tanzania
The validation data collected by the students is closer to the ESA-climate change initiative (CCI) product only when theconsidering mosaic cropland classes, values which of would raise the amount ofNote cropland found the maximum the student validations
Summary
To ensure global food security, cropland is regularly monitored by initiatives such as GEOGLAM (Group on Earth Observation’s Global Agricultural Monitoring) [1], CropWatch [2], and the MARS (Monitoring Agricultural Resources) unit of the Joint Research Centre of the European Commission, among others [3]. Medium to coarse resolution imagery from sensors such as AVHRR, SPOT-VGT, MERIS, and MODIS has been used extensively to map land cover, e.g., [6,7,8] and cropland, e.g., [1,9,10]. These products are mostly generated using a top down approach, employing automated or semi-automated classification techniques and a training data sample collected from field data, interpretation of satellite or aerial imagery, or both. When these products are compared, there are often large spatial disagreements between them, in the cropland class [11], which has led to the production
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